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  • Steps to Create this Graphic
    • 1. Load Packages & Setup
    • 2. Read in the Data
    • 3. Examine the Data
    • 4. Tidy Data
    • 5. Visualization Parameters
    • 6. Plot
    • 7. Save
    • 8. Session Info
    • 9. GitHub Repository
    • 10. References
    • 11. Custom Functions Documentation

From Seed to Table: How Long Until Harvest?

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Median time to harvest by plant family. Light green = germination period, dark green = growing period. ● Sprouted, ● Harvest ready. Gray bars show variability (interquartile range).

TidyTuesday
Data Visualization
R Programming
2026
A horizontal bar chart visualizing median growing timelines for nine edible plant families, from planting to harvest. Chenopods are the fastest at 55 days while Alliums take the longest at 110 days. Built with R and ggplot2 using data from the GROW Observatory Edible Plant Database.
Author

Steven Ponce

Published

February 1, 2026

Figure 1: Bar chart showing harvest timelines for 9 plant families. Chenopods are fastest (55 days), Alliums slowest (110 days). Light green = germination, dark green = growing period. Gray bars show variability. Source: GROW Observatory.

Steps to Create this Graphic

1. Load Packages & Setup

Show code
```{r}
#| label: load
#| warning: false
#| message: false
#| results: "hide"

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse, ggtext, showtext, janitor, 
    scales, glue, patchwork, ineq, ggrepel
)
})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 10,
  height = 7,
  units  = "in",
  dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

2. Read in the Data

Show code
```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false

tt <- tidytuesdayR::tt_load(2026, week = 05)
edible_plants <- tt$edible_plants |> clean_names()
rm(tt)
```

3. Examine the Data

Show code
```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(edible_plants)
```

4. Tidy Data

Show code
```{r}
#| label: tidy
#| warning: false

# Helper: parse numeric ranges like "55-75", "55 – 75"...
parse_range <- function(x, return = c("midpoint", "lower", "upper")) {
  return <- match.arg(return)

  map_dbl(x, function(val) {
    if (is.na(val) || val == "") {
      return(NA_real_)
    }

    val <- str_trim(val)
    val <- str_to_lower(val)

    # Standardize separators
    val <- str_replace_all(val, c("–" = "-", "—" = "-", " to " = "-", "–" = "-"))
    val <- str_replace_all(val, "[^0-9\\.-]+", "") # keep digits, dot, dash

    # Handle "~75" style after stripping non-numeric (becomes "75")
    if (str_detect(val, "^\\d+\\.?\\d*\\+$")) {
      num <- as.numeric(str_remove(val, "\\+$"))
      return(case_when(
        return == "midpoint" ~ num,
        return == "lower" ~ num,
        return == "upper" ~ NA_real_
      ))
    }

    if (str_detect(val, "^\\d+\\.?\\d*-$")) {
      num <- as.numeric(str_remove(val, "-$"))
      return(case_when(
        return == "midpoint" ~ num,
        return == "lower" ~ num,
        return == "upper" ~ NA_real_
      ))
    }

    # Normal range "55-75"
    if (str_detect(val, "-")) {
      parts <- str_split(val, "-", n = 2)[[1]] |>
        str_trim() |>
        as.numeric()

      parts <- parts[!is.na(parts)]

      if (length(parts) == 2) {
        lo <- parts[1]
        hi <- parts[2]
        return(case_when(
          return == "midpoint" ~ mean(c(lo, hi)),
          return == "lower" ~ lo,
          return == "upper" ~ hi
        ))
      }

      if (length(parts) == 1) {
        return(parts[1])
      }
    }

    suppressWarnings(as.numeric(val))
  })
}

plants_clean <- edible_plants |>
  mutate(
    cultivation_clean = case_when(
      str_to_lower(cultivation) %in% c("legume") ~ "Legumes",
      str_to_lower(cultivation) %in% c("brassica", "brassicas") ~ "Brassicas",
      str_to_lower(cultivation) %in% c("allium") ~ "Alliums",
      str_to_lower(cultivation) %in% c("cucurbit") ~ "Cucurbits",
      str_to_lower(cultivation) %in% c("solanaceae", "solanum") ~ "Nightshades",
      str_to_lower(cultivation) %in% c("umbelliferae") ~ "Umbellifers",
      str_to_lower(cultivation) %in% c("lamiaceae") ~ "Herbs",
      str_to_lower(cultivation) %in% c("chenopodiaceae") ~ "Chenopods",
      str_to_lower(cultivation) %in% c("salad") ~ "Salad Greens",
      TRUE ~ "Other"
    ),
    days_harvest_mid = parse_range(days_harvest, "midpoint"),
    days_harvest_low = parse_range(days_harvest, "lower"),
    days_harvest_high = parse_range(days_harvest, "upper"),
    days_germ_mid = parse_range(days_germination, "midpoint")
  )

plot_data <- plants_clean |>
  filter(
    cultivation_clean != "Other",
    !is.na(days_germ_mid),
    !is.na(days_harvest_mid)
  ) |>
  group_by(cultivation_clean) |>
  summarise(
    germ_median = median(days_germ_mid, na.rm = TRUE),
    harvest_median = median(days_harvest_mid, na.rm = TRUE),
    harvest_q25 = quantile(days_harvest_mid, 0.25, na.rm = TRUE),
    harvest_q75 = quantile(days_harvest_mid, 0.75, na.rm = TRUE),
    n = n(),
    .groups = "drop"
  ) |>
  filter(n >= 3) |>
  mutate(
    growing_days = pmax(0, harvest_median - germ_median),
    cult_label = glue("{cultivation_clean} (n={n})"),
    # Longest at top
    cult_label = fct_reorder(cult_label, harvest_median, .desc = TRUE),
    is_anchor = cult_label %in% c(
      "Chenopods (n=3)",
      "Alliums (n=7)"
    )
  )

# Dynamic x-range
x_max <- max(plot_data$harvest_q75, plot_data$harvest_median, na.rm = TRUE)
x_pad <- max(10, round(0.12 * x_max))
x_lim <- c(0, x_max + x_pad)
```

5. Visualization Parameters

Show code
```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = list(
      col_germination = "#A5D6A7",
      col_growing = "#2E7D32",
      col_sprout = "#FFC107",
      col_harvest = "#D32F2F",
      col_iqr = "gray80",
      col_grid = "gray85"
  )
)

### |- titles and caption ----
title_text <- "From Seed to Table: How Long Until Harvest?"

subtitle_text <- str_glue(
    "Median time to harvest by plant family. ",
    "<span style='color:{colors$palette$col_germination};'>**Light green**</span> = germination period, ",
    "<span style='color:{colors$palette$col_growing};'>**dark green**</span> = growing period.<br>",
    "<span style='color:{colors$palette$col_sprout};'>**●**</span> Sprouted, ",
    "<span style='color:{colors$palette$col_harvest};'>**●**</span> Harvest ready. ",
    "Gray bars show variability (interquartile range)."
)

caption_text <- create_social_caption(
    tt_year = 2026,
    tt_week = 05,
    source_text = "GROW Observatory Edible Plant Database"
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----
# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Text styling
    plot.title = element_text(
      face = "bold", family = fonts$title, size = rel(1.4),
      color = colors$title, margin = margin(b = 10), hjust = 0
    ),
    plot.subtitle = element_markdown(
      face = "italic", family = fonts$subtitle, lineheight = 1.2,
      color = colors$subtitle, size = rel(0.9), margin = margin(b = 20), hjust = 0
    ),

    # Grid
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.major = element_line(color = "gray90", linewidth = 0.25),

    # Axes
    axis.title = element_text(size = rel(0.8), color = "gray30"),
    axis.text = element_text(color = "gray30"),
    axis.text.y = element_text(size = rel(0.85)),
    axis.ticks = element_blank(),

    # Facets
    strip.background = element_rect(fill = "gray95", color = NA),
    strip.text = element_text(
      face = "bold",
      color = "gray20",
      size = rel(0.9),
      margin = margin(t = 6, b = 4)
    ),
    panel.spacing = unit(1.5, "lines"),

    # Legend elements
    legend.position = "plot",
    legend.title = element_text(
      family = fonts$subtitle,
      color = colors$text, size = rel(0.8), face = "bold"
    ),
    legend.text = element_text(
      family = fonts$tsubtitle,
      color = colors$text, size = rel(0.7)
    ),
    legend.margin = margin(t = 15),

    # Plot margin
    plot.margin = margin(10, 20, 10, 20),
    
  )
)

# Set theme
theme_set(weekly_theme)
```

6. Plot

Show code
```{r}
#| label: plot
#| warning: false

### |- final plot ----
p <- plot_data |>
    ggplot(aes(y = cult_label)) +
    # Geoms
    geom_vline(
        xintercept = c(30, 60, 90, 120),
        linetype = "dotted",
        color = colors$palette$col_grid,
        linewidth = 0.4, 
        alpha = 0.6
    ) +
    geom_segment(
        aes(x = harvest_q25, xend = harvest_q75, yend = cult_label),
        linewidth = 10,
        color = colors$palette$col_iqr,
        lineend = "round",
        alpha = 0.75
    ) +
    geom_segment(
        aes(x = 0, xend = germ_median, yend = cult_label),
        linewidth = 5,
        color = colors$palette$col_germination,
        lineend = "round"
    ) +
    geom_segment(
        aes(x = germ_median, xend = harvest_median, yend = cult_label),
        linewidth = 5,
        color = colors$palette$col_growing,
        lineend = "round"
    ) +
    geom_point(aes(x = germ_median), size = 4.2, color = colors$palette$col_sprout) +
    geom_point(aes(x = harvest_median), size = 4.2, color = colors$palette$col_harvest) +
    geom_text(
        aes(x = harvest_median, label = glue("{round(harvest_median)} days")),
        hjust = -0.18,
        size = 3.4,
        fontface = "bold",
        color = colors$text,
        family = fonts$subtitle
    ) +
    geom_text(
        aes(
            x = -2,                    
            label = cult_label,
            fontface = if_else(is_anchor, "bold", "plain")
        ),
        hjust = 1,
        family = fonts$subtitle,
        color = "gray30",
        size = 3.5
    ) +
    # Scales
    scale_x_continuous(
        breaks = c(0, 30, 60, 90, 120),
        labels = c("Planted", "1 month", "2 months", "3 months", "4 months"),
        expand = expansion(mult = c(0.02, 0))
    ) +
    scale_y_discrete(NULL, labels = NULL) +
    coord_cartesian(
        xlim = c(-15, x_lim[2]),
        clip = "off"
    ) +
    # Labs
    labs(
        title = title_text,
        subtitle = subtitle_text,
        x = NULL, y = NULL,
        caption = caption_text
  ) +
  # Theme
  theme(
    plot.title = element_markdown(
      size = rel(1.2),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      lineheight = 1.15,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.8),
      family = "sans",
      color = colors$subtitle,
      lineheight = 1.5,
      margin = margin(t = 5, b = 5)
    ),
    plot.caption = element_markdown(
      size = rel(0.55),
      family = fonts$subtitle,
      color = colors$caption,
      hjust = 0,
      lineheight = 1.4,
      margin = margin(t = 10, b = 5)
    )
  )
```

7. Save

Show code
```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot(
  plot = p, 
  type = "tidytuesday", 
  year = 2026, 
  week = 05, 
  width  = 10,
  height = 7,
  )
```

8. Session Info

Expand for Session Info
R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] here_1.0.1      ggrepel_0.9.6   ineq_0.2-13     patchwork_1.3.0
 [5] glue_1.8.0      scales_1.3.0    janitor_2.2.0   showtext_0.9-7 
 [9] showtextdb_3.0  sysfonts_0.8.9  ggtext_0.1.2    lubridate_1.9.3
[13] forcats_1.0.0   stringr_1.5.1   dplyr_1.1.4     purrr_1.0.2    
[17] readr_2.1.5     tidyr_1.3.1     tibble_3.2.1    ggplot2_3.5.1  
[21] tidyverse_2.0.0 pacman_0.5.1   

loaded via a namespace (and not attached):
 [1] gtable_0.3.6       httr2_1.0.6        xfun_0.49          htmlwidgets_1.6.4 
 [5] gh_1.4.1           tzdb_0.5.0         vctrs_0.6.5        tools_4.4.0       
 [9] generics_0.1.3     parallel_4.4.0     curl_6.0.0         gifski_1.32.0-1   
[13] fansi_1.0.6        pkgconfig_2.0.3    lifecycle_1.0.4    compiler_4.4.0    
[17] farver_2.1.2       textshaping_0.4.0  munsell_0.5.1      codetools_0.2-20  
[21] snakecase_0.11.1   htmltools_0.5.8.1  yaml_2.3.10        crayon_1.5.3      
[25] pillar_1.9.0       camcorder_0.1.0    magick_2.8.5       commonmark_1.9.2  
[29] tidyselect_1.2.1   digest_0.6.37      stringi_1.8.4      rsvg_2.6.1        
[33] rprojroot_2.0.4    fastmap_1.2.0      grid_4.4.0         colorspace_2.1-1  
[37] cli_3.6.4          magrittr_2.0.3     utf8_1.2.4         withr_3.0.2       
[41] rappdirs_0.3.3     bit64_4.5.2        timechange_0.3.0   rmarkdown_2.29    
[45] tidytuesdayR_1.1.2 gitcreds_0.1.2     bit_4.5.0          ragg_1.3.3        
[49] hms_1.1.3          evaluate_1.0.1     knitr_1.49         markdown_1.13     
[53] rlang_1.1.6        gridtext_0.1.5     Rcpp_1.0.13-1      xml2_1.3.6        
[57] renv_1.0.3         vroom_1.6.5        svglite_2.1.3      rstudioapi_0.17.1 
[61] jsonlite_1.8.9     R6_2.5.1           systemfonts_1.1.0 

9. GitHub Repository

Expand for GitHub Repo

The complete code for this analysis is available in tt_2026_05.qmd.

For the full repository, click here.

10. References

Expand for References
  1. Data Source:
    • TidyTuesday 2026 Week 05: Edible Plants Database

11. Custom Functions Documentation

📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

Functions Used:

  • fonts.R: setup_fonts(), get_font_families() - Font management with showtext
  • social_icons.R: create_social_caption() - Generates formatted social media captions
  • image_utils.R: save_plot() - Consistent plot saving with naming conventions
  • base_theme.R: create_base_theme(), extend_weekly_theme(), get_theme_colors() - Custom ggplot2 themes

Why custom functions?
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

Source Code:
View all custom functions → GitHub: R/utils

Back to top

Citation

BibTeX citation:
@online{ponce2026,
  author = {Ponce, Steven},
  title = {From {Seed} to {Table:} {How} {Long} {Until} {Harvest?}},
  date = {2026-02-01},
  url = {https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2026/tt_2026_05.html},
  langid = {en}
}
For attribution, please cite this work as:
Ponce, Steven. 2026. “From Seed to Table: How Long Until Harvest?” February 1, 2026. https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2026/tt_2026_05.html.
Source Code
---
title: "From Seed to Table: How Long Until Harvest?"
subtitle: "Median time to harvest by plant family. Light green = germination period, dark green = growing period. ● Sprouted, ● Harvest ready. Gray bars show variability (interquartile range)."
description: "A horizontal bar chart visualizing median growing timelines for nine edible plant families, from planting to harvest. Chenopods are the fastest at 55 days while Alliums take the longest at 110 days. Built with R and ggplot2 using data from the GROW Observatory Edible Plant Database."
date: "2026-02-01"
author:
  - name: "Steven Ponce"
    url: "https://stevenponce.netlify.app"
citation:
  url: "https://stevenponce.netlify.app/data_visualizations/TidyTuesday/2026/tt_2026_05.html" 
categories: ["TidyTuesday", "Data Visualization", "R Programming", "2026"]
tags: [
  "Edible Plants",
  "Gardening",
  "Growing Timeline",
  "Plant Families",
  "GROW Observatory",
  "Horizontal Bar Chart",
  "Timeline Visualization",
  "ggplot2",
  "Data Wrangling"
]
image: "thumbnails/tt_2026_05.png"
format:
  html:
    toc: true
    toc-depth: 5
    code-link: true
    code-fold: true
    code-tools: true
    code-summary: "Show code"
    self-contained: true
    theme: 
      light: [flatly, assets/styling/custom_styles.scss]
      dark: [darkly, assets/styling/custom_styles_dark.scss]
editor_options: 
  chunk_output_type: inline
execute: 
  freeze: true                                    
  cache: true                                       
  error: false
  message: false
  warning: false
  eval: true
---

![Bar chart showing harvest timelines for 9 plant families. Chenopods are fastest (55 days), Alliums slowest (110 days). Light green = germination, dark green = growing period. Gray bars show variability. Source: GROW Observatory.](tt_2026_05.png){#fig-1}

### [**Steps to Create this Graphic**]{.mark}

#### [1. Load Packages & Setup]{.smallcaps}

```{r}
#| label: load
#| warning: false
#| message: false      
#| results: "hide"     

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse, ggtext, showtext, janitor, 
    scales, glue, patchwork, ineq, ggrepel
)
})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 10,
  height = 7,
  units  = "in",
  dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

#### [2. Read in the Data]{.smallcaps}

```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false

tt <- tidytuesdayR::tt_load(2026, week = 05)
edible_plants <- tt$edible_plants |> clean_names()
rm(tt)
```

#### [3. Examine the Data]{.smallcaps}

```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(edible_plants)
```

#### [4. Tidy Data]{.smallcaps}

```{r}
#| label: tidy
#| warning: false

# Helper: parse numeric ranges like "55-75", "55 – 75"...
parse_range <- function(x, return = c("midpoint", "lower", "upper")) {
  return <- match.arg(return)

  map_dbl(x, function(val) {
    if (is.na(val) || val == "") {
      return(NA_real_)
    }

    val <- str_trim(val)
    val <- str_to_lower(val)

    # Standardize separators
    val <- str_replace_all(val, c("–" = "-", "—" = "-", " to " = "-", "–" = "-"))
    val <- str_replace_all(val, "[^0-9\\.-]+", "") # keep digits, dot, dash

    # Handle "~75" style after stripping non-numeric (becomes "75")
    if (str_detect(val, "^\\d+\\.?\\d*\\+$")) {
      num <- as.numeric(str_remove(val, "\\+$"))
      return(case_when(
        return == "midpoint" ~ num,
        return == "lower" ~ num,
        return == "upper" ~ NA_real_
      ))
    }

    if (str_detect(val, "^\\d+\\.?\\d*-$")) {
      num <- as.numeric(str_remove(val, "-$"))
      return(case_when(
        return == "midpoint" ~ num,
        return == "lower" ~ num,
        return == "upper" ~ NA_real_
      ))
    }

    # Normal range "55-75"
    if (str_detect(val, "-")) {
      parts <- str_split(val, "-", n = 2)[[1]] |>
        str_trim() |>
        as.numeric()

      parts <- parts[!is.na(parts)]

      if (length(parts) == 2) {
        lo <- parts[1]
        hi <- parts[2]
        return(case_when(
          return == "midpoint" ~ mean(c(lo, hi)),
          return == "lower" ~ lo,
          return == "upper" ~ hi
        ))
      }

      if (length(parts) == 1) {
        return(parts[1])
      }
    }

    suppressWarnings(as.numeric(val))
  })
}

plants_clean <- edible_plants |>
  mutate(
    cultivation_clean = case_when(
      str_to_lower(cultivation) %in% c("legume") ~ "Legumes",
      str_to_lower(cultivation) %in% c("brassica", "brassicas") ~ "Brassicas",
      str_to_lower(cultivation) %in% c("allium") ~ "Alliums",
      str_to_lower(cultivation) %in% c("cucurbit") ~ "Cucurbits",
      str_to_lower(cultivation) %in% c("solanaceae", "solanum") ~ "Nightshades",
      str_to_lower(cultivation) %in% c("umbelliferae") ~ "Umbellifers",
      str_to_lower(cultivation) %in% c("lamiaceae") ~ "Herbs",
      str_to_lower(cultivation) %in% c("chenopodiaceae") ~ "Chenopods",
      str_to_lower(cultivation) %in% c("salad") ~ "Salad Greens",
      TRUE ~ "Other"
    ),
    days_harvest_mid = parse_range(days_harvest, "midpoint"),
    days_harvest_low = parse_range(days_harvest, "lower"),
    days_harvest_high = parse_range(days_harvest, "upper"),
    days_germ_mid = parse_range(days_germination, "midpoint")
  )

plot_data <- plants_clean |>
  filter(
    cultivation_clean != "Other",
    !is.na(days_germ_mid),
    !is.na(days_harvest_mid)
  ) |>
  group_by(cultivation_clean) |>
  summarise(
    germ_median = median(days_germ_mid, na.rm = TRUE),
    harvest_median = median(days_harvest_mid, na.rm = TRUE),
    harvest_q25 = quantile(days_harvest_mid, 0.25, na.rm = TRUE),
    harvest_q75 = quantile(days_harvest_mid, 0.75, na.rm = TRUE),
    n = n(),
    .groups = "drop"
  ) |>
  filter(n >= 3) |>
  mutate(
    growing_days = pmax(0, harvest_median - germ_median),
    cult_label = glue("{cultivation_clean} (n={n})"),
    # Longest at top
    cult_label = fct_reorder(cult_label, harvest_median, .desc = TRUE),
    is_anchor = cult_label %in% c(
      "Chenopods (n=3)",
      "Alliums (n=7)"
    )
  )

# Dynamic x-range
x_max <- max(plot_data$harvest_q75, plot_data$harvest_median, na.rm = TRUE)
x_pad <- max(10, round(0.12 * x_max))
x_lim <- c(0, x_max + x_pad)
```

#### [5. Visualization Parameters]{.smallcaps}

```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = list(
      col_germination = "#A5D6A7",
      col_growing = "#2E7D32",
      col_sprout = "#FFC107",
      col_harvest = "#D32F2F",
      col_iqr = "gray80",
      col_grid = "gray85"
  )
)

### |- titles and caption ----
title_text <- "From Seed to Table: How Long Until Harvest?"

subtitle_text <- str_glue(
    "Median time to harvest by plant family. ",
    "<span style='color:{colors$palette$col_germination};'>**Light green**</span> = germination period, ",
    "<span style='color:{colors$palette$col_growing};'>**dark green**</span> = growing period.<br>",
    "<span style='color:{colors$palette$col_sprout};'>**●**</span> Sprouted, ",
    "<span style='color:{colors$palette$col_harvest};'>**●**</span> Harvest ready. ",
    "Gray bars show variability (interquartile range)."
)

caption_text <- create_social_caption(
    tt_year = 2026,
    tt_week = 05,
    source_text = "GROW Observatory Edible Plant Database"
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----
# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Text styling
    plot.title = element_text(
      face = "bold", family = fonts$title, size = rel(1.4),
      color = colors$title, margin = margin(b = 10), hjust = 0
    ),
    plot.subtitle = element_markdown(
      face = "italic", family = fonts$subtitle, lineheight = 1.2,
      color = colors$subtitle, size = rel(0.9), margin = margin(b = 20), hjust = 0
    ),

    # Grid
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.major = element_line(color = "gray90", linewidth = 0.25),

    # Axes
    axis.title = element_text(size = rel(0.8), color = "gray30"),
    axis.text = element_text(color = "gray30"),
    axis.text.y = element_text(size = rel(0.85)),
    axis.ticks = element_blank(),

    # Facets
    strip.background = element_rect(fill = "gray95", color = NA),
    strip.text = element_text(
      face = "bold",
      color = "gray20",
      size = rel(0.9),
      margin = margin(t = 6, b = 4)
    ),
    panel.spacing = unit(1.5, "lines"),

    # Legend elements
    legend.position = "plot",
    legend.title = element_text(
      family = fonts$subtitle,
      color = colors$text, size = rel(0.8), face = "bold"
    ),
    legend.text = element_text(
      family = fonts$tsubtitle,
      color = colors$text, size = rel(0.7)
    ),
    legend.margin = margin(t = 15),

    # Plot margin
    plot.margin = margin(10, 20, 10, 20),
    
  )
)

# Set theme
theme_set(weekly_theme)
```

#### [6. Plot]{.smallcaps}

```{r}
#| label: plot
#| warning: false

### |- final plot ----
p <- plot_data |>
    ggplot(aes(y = cult_label)) +
    # Geoms
    geom_vline(
        xintercept = c(30, 60, 90, 120),
        linetype = "dotted",
        color = colors$palette$col_grid,
        linewidth = 0.4, 
        alpha = 0.6
    ) +
    geom_segment(
        aes(x = harvest_q25, xend = harvest_q75, yend = cult_label),
        linewidth = 10,
        color = colors$palette$col_iqr,
        lineend = "round",
        alpha = 0.75
    ) +
    geom_segment(
        aes(x = 0, xend = germ_median, yend = cult_label),
        linewidth = 5,
        color = colors$palette$col_germination,
        lineend = "round"
    ) +
    geom_segment(
        aes(x = germ_median, xend = harvest_median, yend = cult_label),
        linewidth = 5,
        color = colors$palette$col_growing,
        lineend = "round"
    ) +
    geom_point(aes(x = germ_median), size = 4.2, color = colors$palette$col_sprout) +
    geom_point(aes(x = harvest_median), size = 4.2, color = colors$palette$col_harvest) +
    geom_text(
        aes(x = harvest_median, label = glue("{round(harvest_median)} days")),
        hjust = -0.18,
        size = 3.4,
        fontface = "bold",
        color = colors$text,
        family = fonts$subtitle
    ) +
    geom_text(
        aes(
            x = -2,                    
            label = cult_label,
            fontface = if_else(is_anchor, "bold", "plain")
        ),
        hjust = 1,
        family = fonts$subtitle,
        color = "gray30",
        size = 3.5
    ) +
    # Scales
    scale_x_continuous(
        breaks = c(0, 30, 60, 90, 120),
        labels = c("Planted", "1 month", "2 months", "3 months", "4 months"),
        expand = expansion(mult = c(0.02, 0))
    ) +
    scale_y_discrete(NULL, labels = NULL) +
    coord_cartesian(
        xlim = c(-15, x_lim[2]),
        clip = "off"
    ) +
    # Labs
    labs(
        title = title_text,
        subtitle = subtitle_text,
        x = NULL, y = NULL,
        caption = caption_text
  ) +
  # Theme
  theme(
    plot.title = element_markdown(
      size = rel(1.2),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      lineheight = 1.15,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.8),
      family = "sans",
      color = colors$subtitle,
      lineheight = 1.5,
      margin = margin(t = 5, b = 5)
    ),
    plot.caption = element_markdown(
      size = rel(0.55),
      family = fonts$subtitle,
      color = colors$caption,
      hjust = 0,
      lineheight = 1.4,
      margin = margin(t = 10, b = 5)
    )
  )
```

#### [7. Save]{.smallcaps}

```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot(
  plot = p, 
  type = "tidytuesday", 
  year = 2026, 
  week = 05, 
  width  = 10,
  height = 7,
  )
```

#### [8. Session Info]{.smallcaps}

::: {.callout-tip collapse="true"}
##### Expand for Session Info

```{r, echo = FALSE}
#| eval: true
#| warning: false

sessionInfo()
```
:::

#### [9. GitHub Repository]{.smallcaps}

::: {.callout-tip collapse="true"}
##### Expand for GitHub Repo

The complete code for this analysis is available in [`tt_2026_05.qmd`](https://github.com/poncest/personal-website/blob/master/data_visualizations/TidyTuesday/2026/tt_2026_05.qmd).

For the full repository, [click here](https://github.com/poncest/personal-website/).
:::

#### [10. References]{.smallcaps}

::: {.callout-tip collapse="true"}
##### Expand for References
1.  **Data Source:**
    -   TidyTuesday 2026 Week 05: [Edible Plants Database](https://github.com/rfordatascience/tidytuesday/blob/main/data/2026/2026-02-03/readme.md)

:::


#### [11. Custom Functions Documentation]{.smallcaps}

::: {.callout-note collapse="true"}
##### 📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

**Functions Used:**

-   **`fonts.R`**: `setup_fonts()`, `get_font_families()` - Font management with showtext
-   **`social_icons.R`**: `create_social_caption()` - Generates formatted social media captions
-   **`image_utils.R`**: `save_plot()` - Consistent plot saving with naming conventions
-   **`base_theme.R`**: `create_base_theme()`, `extend_weekly_theme()`, `get_theme_colors()` - Custom ggplot2 themes

**Why custom functions?**\
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

**Source Code:**\
View all custom functions → [GitHub: R/utils](https://github.com/poncest/personal-website/tree/master/R)
:::

© 2024 Steven Ponce

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